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dc.contributor.authorAcharya, D P-
dc.contributor.authorPanda, G-
dc.identifier.citationIETE Technical Review, Volume 25, Issue 6, 1 November 2008, Pages 320-332en
dc.descriptionCopyright for the published paper belong to the publisheren
dc.description.abstractIndependent Component Analysis, a computationally efficient blind statistical signal processing technique, has been an area of interest for researchers for many practical applications in various fields of science and engineering. The present paper attempts to treat the fundamental concepts involved in the independent component analysis (ICA) technique and reviews different ICA algorithms. A thorough discussion of the algorithms with their merits and weaknesses has been carried out. Applications of the ICA algorithms in different fields of science and technology have been reviewed. The limitations and ambiguities of the ICA techniques developed so far have also been outlined. Though several articles have reviewed the ICA techniques in literature, they suffer from the limitation of not being comprehensive to a first time reader or not incorporating the latest available algorithm and their applications. In this work, we present different ICA algorithms from their basics to their potential applications to serve as a comprehensive single source for an inquisitive researcher to carry out his work in this field. © 2008 by the IETE.en
dc.format.extent552413 bytes-
dc.subjectBlind source separationen
dc.subjectHigher order statisticsen
dc.subjectIndependent component analysisen
dc.titleA Review of Independent Component Analysis Techniques and their Applicationsen
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